1. Field of the Invention
The present invention relates to an image processing apparatus and a method of operation of an image processing apparatus for performing image processing of a medical image picked up of a living mucous membrane.
2. Description of the Related Art
Techniques that, based on a result of calculation of feature values in a medical image obtained by image pickup of a body tissue, divide the medical image into regions to detect a region where a predetermined target object exists have conventionally been used.
For example, Japanese Patent Application Laid-Open Publication No. 2006-141734 discloses a region division technique that, based on image signals resulting from pickup of an image of an object, extracts a living mucous membrane microstructure using binarization processing, performs labelling processing of the binarized image generated by setting pixel values of pixels corresponding to the living mucous membrane microstructure to 1 and pixels other than the pixels to 0, identifying components included in the living mucous membrane microstructure, and allocates regions to the respective components of the living mucous membrane microstructure based on structure information on the respective components.
Also, Japanese Patent Application Laid-Open Publication No. 2011-516200 discloses a technique that automatically traces one or more paths of one or more blood vessels in a retina image, automatically identifies blood vessel segments included in the traced blood vessels, and uses the blood vessel segments to calculate feature values of the blood vessels.
Also, in recent years, with the increase in resolution of endoscope (which may be capsule endoscope) systems, the popularization of magnifying endoscopes and the popularization of narrow-band light observation, observation of living mucous membrane microstructures such as microscopic blood vessel images and pit structures has been growing in importance.
Information on the forms and distribution of living mucous membrane microstructures in a body tissue is useful for discrimination between normal tissues and tumor tissues, and further for diagnosis of a lesion such as estimation of a penetration depth of a cancer. For these living mucous membrane microstructure findings, diagnostics based on various classifications for various organs and diseases is proposed and used. For example, large intestine pit pattern observation (see, for example, “Early-Stage Depressed Large Intestine Cancer”, Eishin Kudo, Monthly Book Gastro, Kabushikigaisha Zen-nihon Byo-in Shuppan-kai, May 15, 1993, third volume, fifth issue, p.p. 47-54), MV Pattern, which is a microscopic blood vessel finding in a mucous membrane of a stomach, and MS Pattern, which is a mucous membrane surface microscopic structure (epithelial structure) finding (see, for example, “Zoom Gastroscopy” (2009), Kenshi Yao and Toshiyuki Matsui) and IPCL, which is a microscopic blood vessel finding in a mucous membrane in an esophagus (see, for example, “magnifying endoscopic diagnosis of esophageal diseases”, Haruhiro Inoue and five others, Gastroenterological Endoscopy, Kabushiki Kaisha Tokyo Igakusha, Mar. 25, 2001, 13-th issue, third issue, p.p. 301-308) are known. Also, blood vessel findings in bronchi are drawing attention although there is no clear category for such blood vessel findings.
However, since such diagnoses are based mainly on the experience and knowledge of the respective doctors, as a technique for eliminating differences in experience and knowledge, for example, there is a demand for providing a differential diagnosis support technique for living mucous membrane microstructure findings using an image analysis technique. Such differential diagnosis support technique is being studied as one of computer-aided diagnoses (CAD).
For example, in a diagnosis using an MV pattern and an MS pattern of a stomach, shape uniformity, arrangement regularity and distribution symmetry in each pattern (figure) can be important findings. These findings can be identified not directly from an image one can see, but, for example, with some kind of interpretation added thereto, such as estimating and analyzing a three-dimensional histological structure of a living mucous membrane from a visible endoscopic image.
Through such process of adding some kind of interpretation, a finding that is a target of identification may vary in such a manner that the finding is sometimes an entire pattern and sometimes only a partial pattern in an image.
In analysis of a living mucous membrane microstructure in an endoscopic image, it is essential not to simply analyze a continuous pattern one can see, but analyze a pattern corresponding to a finding by adding some kind of interpretation to the pattern.